Inference in hidden Markov models

✍ Scribed by Cappé, Olivier; Moulines, Eric; Rydén, Tobias

Publisher: Springer
Year: 2005
Tongue: English
Leaves: 668
Series: Springer series in statistics
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.

✦ Table of Contents

Content: 1. Introduction --
2. Main definitions and notations --
Pt. I. State inference --
3. Filtering and smoothing recursions --
4. Advanced topics in smoothing --
5. Applications of smoothing --
6. Monte Carlo methods --
7. Sequential Monte Carlo methods --
8. Advanced topics in sequential Monte Carlo --
9. Analysis of sequential Monte Carlo methods --
Pt. II. Parameter inference --
10. Maximum likelihood inference, part I : optimization through exact smoothing --
11. Maximum likelihood inference, part II : Monte Carlo optimization --
12. Statistical properties of the maximum likelihood estimator --
13. Fully Bayesian approaches --
Pt. III. Background and complements --
14. Elements of Markov chain theory --
15. An information-theoretic perspective on order estimation --
App. A. Conditioning --
App. B. Linear prediction --
App. C. Notations.

✦ Subjects

Markov processes.;Markov, Processus de.;Markov-modellen.;Matematisk statistik.

📜 SIMILAR VOLUMES

Inference in Hidden Markov Models

📁 Inference in Hidden Markov Models

✍ Olivier Cappé, Eric Moulines, Tobias Ryden 📂 Library 📅 2005 🏛 Springer, Berlin 🌐 English

<P>This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way t

Inference in hidden Markov models

📁 Inference in hidden Markov models

✍ Cappe O., Moulines E., Ryden T. 📂 Library 📅 2005 🏛 Springer 🌐 English

Inference in Hidden Markov Models

📁 Inference in Hidden Markov Models

✍ Olivier Cappé, Eric Moulines, Tobias Ryden 📂 Library 📅 2005 🏛 Springer 🌐 English

Inference in Hidden Markov Models

📁 Inference in Hidden Markov Models

✍ Olivier Cappé, Eric Moulines, Tobias Ryden 📂 Library 📅 2005 🏛 Springer 🌐 English

Hidden Markov models have become a widely used class of statistical models with applications in diverse areas such as communications engineering, bioinformatics, finance and many more. This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statist

Hidden Markov models in finance

📁 Hidden Markov models in finance

✍ Rogemar S. Mamon, Robert J. Elliott 📂 Library 📅 2007 🏛 Springer 🌐 English

<P>A number of methodologies have been employed to provide decision making solutions to a whole assortment of financial problems in today's globalized markets. <EM>Hidden Markov Models in Finance</EM> by Mamon and Elliott will be the first systematic application of these methods to some special kind

Hidden Markov Models in Finance

📁 Hidden Markov Models in Finance

✍ Mamon R.S., Elliott R.J. 📂 Library 📅 2007 🌐 English

A number of methodologies have been employed to provide decision making solutions to a whole assortment of financial problems in today's globalized markets. Hidden Markov Models in Finance by Mamon and Elliott will be the first systematic application of these methods to some special kinds of financi